1. Learn
    2. /
  2. Courses
    3. /
  3. RBootcamp
  • 1

    The Magic of ggplot2

    Learn how ggplot2 turns variables into statistical graphics

  • 2

    ggplot2 and categorical data

    More on plotting using ggplot2

  • 3

    Introduction to dplyr

    Learn how to manipulate data into a ggplot2 friendly format

  • 4

    The Whys and Hows of Tidy Data

    Why we need tidy data and using `tidyr` to make messy data tidy

  • 5

    Simple Stats and Modeling with broom

    Now we have tidy data, let's start doing some statistics!

Initializing

Exercise

What you learned in this chapter

  • T.tests and linear regression in R
  • broom functions to make model output tidy
  • How to put it together with dplyr and ggplot2 to assess model fit and visualize results
  • How the tidyverse comes together to make data manipulation and statistics easier

Instructions

100 XP

There are so many directions you can go in now that you know the basics of the tidyverse. Here are some important links for going further.

  • R for Data Science - This is the foundational text for doing data science in R and will take you further in data manipulation
  • Modern Dive - Chester and Albert's short but sweet book on foundational data science skills in R.

Need help with statistics/biostatistics at OHSU? There are some groups on campus that are there for you (they even have drop in hours):

  • Biostatistics & Design Program
  • Knight Biostatistics Shared Resource for Knight Cancer Members

Also take some classes!

  • Biostatistics classes in OHSU-PSU School of Public Health
  • Computational Biology classes in DMICE
  • Probability and Statistical Inference class in CS/EE
  • Biostatistics classes in the Human Investigator Program